Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations1326
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.1 KiB
Average record size in memory88.1 B

Variable types

Numeric11

Alerts

S1 is highly overall correlated with S2High correlation
S11 is highly overall correlated with S8High correlation
S2 is highly overall correlated with S1High correlation
S3 is highly overall correlated with S4 and 1 other fieldsHigh correlation
S4 is highly overall correlated with S3 and 1 other fieldsHigh correlation
S6 is highly overall correlated with S7High correlation
S7 is highly overall correlated with S3 and 2 other fieldsHigh correlation
S8 is highly overall correlated with S11High correlation

Reproduction

Analysis started2024-12-16 05:05:19.635745
Analysis finished2024-12-16 05:05:33.548145
Duration13.91 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

S11
Real number (ℝ)

High correlation 

Distinct127
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.788084
Minimum1
Maximum855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:33.630456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile83
Maximum855
Range854
Interquartile range (IQR)1

Descriptive statistics

Standard deviation49.362452
Coefficient of variation (CV)3.3379882
Kurtosis91.615006
Mean14.788084
Median Absolute Deviation (MAD)0
Skewness7.8043989
Sum19609
Variance2436.6517
MonotonicityNot monotonic
2024-12-16T08:35:33.797812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 971
73.2%
2 27
 
2.0%
3 16
 
1.2%
5 16
 
1.2%
6 14
 
1.1%
4 12
 
0.9%
11 9
 
0.7%
22 9
 
0.7%
9 8
 
0.6%
10 8
 
0.6%
Other values (117) 236
 
17.8%
ValueCountFrequency (%)
1 971
73.2%
2 27
 
2.0%
3 16
 
1.2%
4 12
 
0.9%
5 16
 
1.2%
6 14
 
1.1%
7 7
 
0.5%
8 8
 
0.6%
9 8
 
0.6%
10 8
 
0.6%
ValueCountFrequency (%)
855 1
0.1%
600 1
0.1%
432 1
0.1%
366 1
0.1%
343 1
0.1%
332 1
0.1%
311 1
0.1%
302 1
0.1%
288 1
0.1%
287 1
0.1%

S8
Real number (ℝ)

High correlation 

Distinct353
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.385735
Minimum8.2896904
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:34.089212image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.2896904
5-th percentile92.004923
Q199.995376
median100
Q3100
95-th percentile100
Maximum100
Range91.71031
Interquartile range (IQR)0.0046243225

Descriptive statistics

Standard deviation7.0754454
Coefficient of variation (CV)0.071915359
Kurtosis49.882334
Mean98.385735
Median Absolute Deviation (MAD)0
Skewness-6.4699759
Sum130459.48
Variance50.061928
MonotonicityNot monotonic
2024-12-16T08:35:34.223643image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 974
73.5%
99.73805984 1
 
0.1%
92.78767735 1
 
0.1%
92.49788809 1
 
0.1%
99.98534147 1
 
0.1%
99.99501312 1
 
0.1%
99.0827383 1
 
0.1%
99.48552783 1
 
0.1%
97.79423045 1
 
0.1%
98.77994645 1
 
0.1%
Other values (343) 343
 
25.9%
ValueCountFrequency (%)
8.289690412 1
0.1%
31.58468281 1
0.1%
39.21613953 1
0.1%
41.96564552 1
0.1%
44.63212926 1
0.1%
45.67299582 1
0.1%
46.02028808 1
0.1%
50.90937821 1
0.1%
51.64372875 1
0.1%
53.35694574 1
0.1%
ValueCountFrequency (%)
100 974
73.5%
99.99946729 1
 
0.1%
99.99890278 1
 
0.1%
99.99879574 1
 
0.1%
99.99876814 1
 
0.1%
99.99823626 1
 
0.1%
99.99813084 1
 
0.1%
99.99809721 1
 
0.1%
99.9978424 1
 
0.1%
99.99779285 1
 
0.1%

S9
Real number (ℝ)

Distinct1325
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0016249837
Minimum-0.066890722
Maximum0.001173667
Zeros0
Zeros (%)0.0%
Negative1272
Negative (%)95.9%
Memory size10.5 KiB
2024-12-16T08:35:34.359454image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-0.066890722
5-th percentile-0.0043392967
Q1-0.001984995
median-0.0009681555
Q3-0.00054172375
95-th percentile-7.3575 × 10-5
Maximum0.001173667
Range0.068064389
Interquartile range (IQR)0.0014432712

Descriptive statistics

Standard deviation0.0032581692
Coefficient of variation (CV)-2.0050473
Kurtosis222.55167
Mean-0.0016249837
Median Absolute Deviation (MAD)0.000564061
Skewness-13.17971
Sum-2.1547284
Variance1.0615667 × 10-5
MonotonicityNot monotonic
2024-12-16T08:35:34.494924image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.001651001 2
 
0.2%
-0.000268705 1
 
0.1%
-0.000390013 1
 
0.1%
-0.002821197 1
 
0.1%
-0.001291129 1
 
0.1%
-0.024657982 1
 
0.1%
-0.003281615 1
 
0.1%
-0.000463627 1
 
0.1%
-0.001045463 1
 
0.1%
-0.000914062 1
 
0.1%
Other values (1315) 1315
99.2%
ValueCountFrequency (%)
-0.066890722 1
0.1%
-0.05560991 1
0.1%
-0.05073383 1
0.1%
-0.028058535 1
0.1%
-0.024657982 1
0.1%
-0.022288464 1
0.1%
-0.018735594 1
0.1%
-0.012260422 1
0.1%
-0.009537443 1
0.1%
-0.00860833 1
0.1%
ValueCountFrequency (%)
0.001173667 1
0.1%
0.000898844 1
0.1%
0.000897719 1
0.1%
0.000893472 1
0.1%
0.000856678 1
0.1%
0.00084308 1
0.1%
0.000823255 1
0.1%
0.000819013 1
0.1%
0.000791728 1
0.1%
0.000685435 1
0.1%

S10
Real number (ℝ)

Distinct1030
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.3558424 × 10-6
Minimum-4.06 × 10-5
Maximum8.83 × 10-6
Zeros0
Zeros (%)0.0%
Negative590
Negative (%)44.5%
Memory size10.5 KiB
2024-12-16T08:35:34.635811image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4.06 × 10-5
5-th percentile-1.7575 × 10-5
Q1-1.9675 × 10-6
median1.04 × 10-7
Q36.285 × 10-7
95-th percentile2.2575 × 10-6
Maximum8.83 × 10-6
Range4.943 × 10-5
Interquartile range (IQR)2.596 × 10-6

Descriptive statistics

Standard deviation6.317937 × 10-6
Coefficient of variation (CV)-2.6818165
Kurtosis5.1036477
Mean-2.3558424 × 10-6
Median Absolute Deviation (MAD)7.81 × 10-7
Skewness-2.2767242
Sum-0.003123847
Variance3.9916328 × 10-11
MonotonicityNot monotonic
2024-12-16T08:35:34.773143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.67 × 10-56
 
0.5%
-2.01 × 10-66
 
0.5%
1.31 × 10-65
 
0.4%
2.23 × 10-75
 
0.4%
1.09 × 10-64
 
0.3%
1.41 × 10-64
 
0.3%
1.02 × 10-64
 
0.3%
1.13 × 10-64
 
0.3%
-2 × 10-54
 
0.3%
-1.79 × 10-54
 
0.3%
Other values (1020) 1280
96.5%
ValueCountFrequency (%)
-4.06 × 10-51
0.1%
-3.34 × 10-51
0.1%
-3.05 × 10-51
0.1%
-3.02 × 10-51
0.1%
-2.97 × 10-51
0.1%
-2.86 × 10-51
0.1%
-2.83 × 10-51
0.1%
-2.74 × 10-51
0.1%
-2.72 × 10-51
0.1%
-2.68 × 10-51
0.1%
ValueCountFrequency (%)
8.83 × 10-61
0.1%
8.57 × 10-61
0.1%
8.37 × 10-61
0.1%
6.64 × 10-61
0.1%
6.18 × 10-61
0.1%
6.04 × 10-61
0.1%
6.01 × 10-61
0.1%
5.62 × 10-61
0.1%
5.56 × 10-61
0.1%
5.32 × 10-61
0.1%

S2
Real number (ℝ)

High correlation 

Distinct285
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00014409125
Minimum3.6 × 10-5
Maximum0.004135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:34.903593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.6 × 10-5
5-th percentile6.2 × 10-5
Q18.9 × 10-5
median0.000117
Q30.000162
95-th percentile0.000287
Maximum0.004135
Range0.004099
Interquartile range (IQR)7.3 × 10-5

Descriptive statistics

Standard deviation0.00015406971
Coefficient of variation (CV)1.069251
Kurtosis382.10815
Mean0.00014409125
Median Absolute Deviation (MAD)3.4 × 10-5
Skewness16.434495
Sum0.191065
Variance2.3737476 × 10-8
MonotonicityNot monotonic
2024-12-16T08:35:35.045043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.1 × 10-518
 
1.4%
0.000101 18
 
1.4%
0.0001 17
 
1.3%
9.4 × 10-517
 
1.3%
9.5 × 10-516
 
1.2%
9.1 × 10-516
 
1.2%
9.6 × 10-515
 
1.1%
9.9 × 10-515
 
1.1%
9 × 10-515
 
1.1%
0.000142 14
 
1.1%
Other values (275) 1165
87.9%
ValueCountFrequency (%)
3.6 × 10-51
 
0.1%
4 × 10-51
 
0.1%
4.1 × 10-51
 
0.1%
4.4 × 10-54
0.3%
4.5 × 10-53
0.2%
4.6 × 10-52
0.2%
4.8 × 10-51
 
0.1%
4.9 × 10-51
 
0.1%
5 × 10-52
0.2%
5.1 × 10-54
0.3%
ValueCountFrequency (%)
0.004135 1
0.1%
0.002496 1
0.1%
0.001179 1
0.1%
0.000799 1
0.1%
0.000655 1
0.1%
0.000649 1
0.1%
0.000619 1
0.1%
0.000579 1
0.1%
0.000577 1
0.1%
0.00057 1
0.1%

S1
Real number (ℝ)

High correlation 

Distinct1325
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8967.6071
Minimum241.797
Maximum27233.913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:35.193778image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum241.797
5-th percentile3481.7076
Q16150.8358
median8524.3437
Q311202.792
95-th percentile15984.99
Maximum27233.913
Range26992.116
Interquartile range (IQR)5051.9567

Descriptive statistics

Standard deviation3903.5125
Coefficient of variation (CV)0.43529031
Kurtosis0.88619766
Mean8967.6071
Median Absolute Deviation (MAD)2493.5269
Skewness0.7390841
Sum11891047
Variance15237410
MonotonicityNot monotonic
2024-12-16T08:35:35.343535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7550.453716 2
 
0.2%
7548.302224 1
 
0.1%
13819.59911 1
 
0.1%
8909.441211 1
 
0.1%
10525.31035 1
 
0.1%
8489.973635 1
 
0.1%
8209.118072 1
 
0.1%
14356.75115 1
 
0.1%
6777.437231 1
 
0.1%
14367.34949 1
 
0.1%
Other values (1315) 1315
99.2%
ValueCountFrequency (%)
241.797004 1
0.1%
400.563489 1
0.1%
847.673185 1
0.1%
1251.491987 1
0.1%
1525.738783 1
0.1%
1540.00716 1
0.1%
1613.274142 1
0.1%
1726.946044 1
0.1%
1730.552161 1
0.1%
1753.162171 1
0.1%
ValueCountFrequency (%)
27233.91253 1
0.1%
24881.23625 1
0.1%
24151.12254 1
0.1%
22588.17855 1
0.1%
22512.33387 1
0.1%
22356.81857 1
0.1%
22352.13426 1
0.1%
22066.11231 1
0.1%
21912.095 1
0.1%
21850.51095 1
0.1%

S3
Real number (ℝ)

High correlation 

Distinct1204
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.41128824
Minimum0.0011
Maximum0.8235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:35.478574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.0011
5-th percentile0.08285
Q10.287125
median0.42485
Q30.55345
95-th percentile0.682675
Maximum0.8235
Range0.8224
Interquartile range (IQR)0.266325

Descriptive statistics

Standard deviation0.18190135
Coefficient of variation (CV)0.44227218
Kurtosis-0.68588192
Mean0.41128824
Median Absolute Deviation (MAD)0.1326
Skewness-0.27750258
Sum545.3682
Variance0.033088099
MonotonicityNot monotonic
2024-12-16T08:35:35.610302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4079 3
 
0.2%
0.4627 3
 
0.2%
0.5137 3
 
0.2%
0.3963 3
 
0.2%
0.4679 3
 
0.2%
0.4755 3
 
0.2%
0.4008 3
 
0.2%
0.3686 3
 
0.2%
0.3274 3
 
0.2%
0.6122 2
 
0.2%
Other values (1194) 1297
97.8%
ValueCountFrequency (%)
0.0011 1
0.1%
0.0015 1
0.1%
0.0016 1
0.1%
0.0047 1
0.1%
0.0065 1
0.1%
0.0088 1
0.1%
0.0101 1
0.1%
0.0104 1
0.1%
0.0106 1
0.1%
0.0125 1
0.1%
ValueCountFrequency (%)
0.8235 1
0.1%
0.8213 1
0.1%
0.8006 1
0.1%
0.7847 1
0.1%
0.7786 1
0.1%
0.7743 1
0.1%
0.7686 1
0.1%
0.7625 1
0.1%
0.7621 1
0.1%
0.7598 1
0.1%

S4
Real number (ℝ)

High correlation 

Distinct1283
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18969932
Minimum0
Maximum0.87892
Zeros5
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:35.740005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.001105
Q10.0273
median0.112825
Q30.2873975
95-th percentile0.6110275
Maximum0.87892
Range0.87892
Interquartile range (IQR)0.2600975

Descriptive statistics

Standard deviation0.19866699
Coefficient of variation (CV)1.0472731
Kurtosis0.59313922
Mean0.18969932
Median Absolute Deviation (MAD)0.10425
Skewness1.1734262
Sum251.5413
Variance0.039468574
MonotonicityNot monotonic
2024-12-16T08:35:35.864986image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
0.4%
8 × 10-53
 
0.2%
3 × 10-53
 
0.2%
0.00039 3
 
0.2%
0.0093 2
 
0.2%
0.00178 2
 
0.2%
0.00056 2
 
0.2%
0.41969 2
 
0.2%
0.1696 2
 
0.2%
0.04022 2
 
0.2%
Other values (1273) 1300
98.0%
ValueCountFrequency (%)
0 5
0.4%
1 × 10-51
 
0.1%
2 × 10-52
 
0.2%
3 × 10-53
0.2%
4 × 10-52
 
0.2%
5 × 10-51
 
0.1%
6 × 10-51
 
0.1%
7 × 10-51
 
0.1%
8 × 10-53
0.2%
9 × 10-52
 
0.2%
ValueCountFrequency (%)
0.87892 1
0.1%
0.85789 1
0.1%
0.85383 1
0.1%
0.84718 1
0.1%
0.84105 1
0.1%
0.83788 1
0.1%
0.83486 1
0.1%
0.81786 1
0.1%
0.8131 1
0.1%
0.79284 1
0.1%

S5
Real number (ℝ)

Distinct1318
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.997027
Minimum14.8917
Maximum169.274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:35.985684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum14.8917
5-th percentile27.534575
Q144.1253
median74.493
Q3136.01525
95-th percentile151.4035
Maximum169.274
Range154.3823
Interquartile range (IQR)91.88995

Descriptive statistics

Standard deviation47.623538
Coefficient of variation (CV)0.5291679
Kurtosis-1.7500104
Mean89.997027
Median Absolute Deviation (MAD)46.53755
Skewness-0.0059295617
Sum119336.06
Variance2268.0014
MonotonicityNot monotonic
2024-12-16T08:35:36.123672image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142.731 2
 
0.2%
147.061 2
 
0.2%
138.541 2
 
0.2%
138.351 2
 
0.2%
123.171 2
 
0.2%
132.21 2
 
0.2%
140.935 2
 
0.2%
147.321 2
 
0.2%
129.018 1
 
0.1%
114.881 1
 
0.1%
Other values (1308) 1308
98.6%
ValueCountFrequency (%)
14.8917 1
0.1%
16.2814 1
0.1%
16.7605 1
0.1%
16.9407 1
0.1%
17.2116 1
0.1%
17.4401 1
0.1%
17.4914 1
0.1%
17.6921 1
0.1%
17.6936 1
0.1%
18.0659 1
0.1%
ValueCountFrequency (%)
169.274 1
0.1%
165.151 1
0.1%
164.518 1
0.1%
163.662 1
0.1%
162.281 1
0.1%
162.059 1
0.1%
161.987 1
0.1%
161.76 1
0.1%
161.709 1
0.1%
161.646 1
0.1%

S7
Real number (ℝ)

High correlation 

Distinct1323
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.63373249
Minimum0.304508
Maximum0.964955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:36.261828image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.304508
5-th percentile0.4372005
Q10.551506
median0.637941
Q30.7222385
95-th percentile0.81319075
Maximum0.964955
Range0.660447
Interquartile range (IQR)0.1707325

Descriptive statistics

Standard deviation0.11513955
Coefficient of variation (CV)0.18168478
Kurtosis-0.51025439
Mean0.63373249
Median Absolute Deviation (MAD)0.085845
Skewness-0.17116077
Sum840.32928
Variance0.013257116
MonotonicityNot monotonic
2024-12-16T08:35:36.396720image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.52366 2
 
0.2%
0.551506 2
 
0.2%
0.761984 2
 
0.2%
0.744465 1
 
0.1%
0.834402 1
 
0.1%
0.485568 1
 
0.1%
0.789898 1
 
0.1%
0.470843 1
 
0.1%
0.820969 1
 
0.1%
0.550045 1
 
0.1%
Other values (1313) 1313
99.0%
ValueCountFrequency (%)
0.304508 1
0.1%
0.3107 1
0.1%
0.325505 1
0.1%
0.334917 1
0.1%
0.33638 1
0.1%
0.338018 1
0.1%
0.342545 1
0.1%
0.344978 1
0.1%
0.352082 1
0.1%
0.356856 1
0.1%
ValueCountFrequency (%)
0.964955 1
0.1%
0.953838 1
0.1%
0.900869 1
0.1%
0.892993 1
0.1%
0.88539 1
0.1%
0.883496 1
0.1%
0.882538 1
0.1%
0.877754 1
0.1%
0.872236 1
0.1%
0.868496 1
0.1%

S6
Real number (ℝ)

High correlation 

Distinct1291
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.28152208
Minimum0
Maximum0.82651
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.5 KiB
2024-12-16T08:35:36.533500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.152325
Q10.215895
median0.2699
Q30.33562
95-th percentile0.443475
Maximum0.82651
Range0.82651
Interquartile range (IQR)0.119725

Descriptive statistics

Standard deviation0.091909819
Coefficient of variation (CV)0.32647464
Kurtosis1.669189
Mean0.28152208
Median Absolute Deviation (MAD)0.0583
Skewness0.80196592
Sum373.29828
Variance0.0084474148
MonotonicityNot monotonic
2024-12-16T08:35:36.658994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.297 3
 
0.2%
0.23475 3
 
0.2%
0.22483 3
 
0.2%
0.27681 2
 
0.2%
0.18916 2
 
0.2%
0.30863 2
 
0.2%
0.20529 2
 
0.2%
0.21205 2
 
0.2%
0.13327 2
 
0.2%
0.23161 2
 
0.2%
Other values (1281) 1303
98.3%
ValueCountFrequency (%)
0 1
0.1%
0.03663 1
0.1%
0.06466 1
0.1%
0.0741 1
0.1%
0.07853 1
0.1%
0.0841 1
0.1%
0.08451 1
0.1%
0.09489 1
0.1%
0.09639 1
0.1%
0.10803 1
0.1%
ValueCountFrequency (%)
0.82651 1
0.1%
0.78054 1
0.1%
0.61319 1
0.1%
0.61201 1
0.1%
0.59909 1
0.1%
0.58617 1
0.1%
0.55959 1
0.1%
0.55762 1
0.1%
0.55304 1
0.1%
0.55095 1
0.1%

Interactions

2024-12-16T08:35:31.986286image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:19.884527image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.021181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.307875image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.521069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.709537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.860814image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.072512image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.386101image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.510046image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.745894image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.099163image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:19.988214image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.118148image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.409007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.620530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.806092image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.964442image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.181663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.489838image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.627915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.846613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.207921image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.089572image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.210776image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.513368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.727166image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.909346image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.072316image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.279710image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.591401image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.727456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.944408image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.349365image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.200606image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.328139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.622028image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.854989image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.024401image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.191210image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.390295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.700260image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.843183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.060117image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.472015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.304807image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.579659image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.739991image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.966968image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.126278image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.309591image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.506187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.796604image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.953041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.180679image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.583885image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.402613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.691326image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.847693image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.071444image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.227343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.403831image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.607059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.895126image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.058027image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.283383image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.695908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.505335image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.808122image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.959976image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.175470image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.337123image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.511775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.711009image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.999867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.183255image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.402386image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.789069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.603848image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.899644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.067945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.279418image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.451079image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.615368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:27.800578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.104139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.296131image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.504967image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.886594image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.707783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:21.996265image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.177227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.383155image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.544603image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.732366image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.071287image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.200057image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.406665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.601594image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:32.999119image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.819111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.096545image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.289571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.499886image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.653122image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.851324image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.180236image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.309726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.520449image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.731044image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:33.126539image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:20.918996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:22.204319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:23.414254image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:24.601024image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:25.768655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:26.969032image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:28.289462image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:29.419524image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:30.643873image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-12-16T08:35:31.858063image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-12-16T08:35:36.893281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
S1S10S11S2S3S4S5S6S7S8S9
S11.000-0.027-0.252-1.000-0.201-0.1210.024-0.311-0.2990.2880.154
S10-0.0271.0000.0810.027-0.010-0.021-0.025-0.0090.008-0.076-0.292
S11-0.2520.0811.0000.2520.0300.0360.0080.1330.102-0.982-0.050
S2-1.0000.0270.2521.0000.2010.121-0.0250.3110.299-0.288-0.154
S3-0.201-0.0100.0300.2011.0000.612-0.0250.3000.838-0.032-0.019
S4-0.121-0.0210.0360.1210.6121.000-0.0150.2720.573-0.0350.011
S50.024-0.0250.008-0.025-0.025-0.0151.000-0.033-0.030-0.007-0.053
S6-0.311-0.0090.1330.3110.3000.272-0.0331.0000.653-0.134-0.052
S7-0.2990.0080.1020.2990.8380.573-0.0300.6531.000-0.103-0.035
S80.288-0.076-0.982-0.288-0.032-0.035-0.007-0.134-0.1031.0000.036
S90.154-0.292-0.050-0.154-0.0190.011-0.053-0.052-0.0350.0361.000

Missing values

2024-12-16T08:35:33.296965image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-12-16T08:35:33.474629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

S11S8S9S10S2S1S3S4S5S7S6
01.0100.000000-0.000269-2.850000e-070.0001327548.3022240.61420.63750124.79100.8344020.52243
11.0100.000000-0.000390-1.150000e-050.00007213819.5991100.06130.07049136.96400.4855680.25631
21.0100.000000-0.002821-6.900000e-070.0001128909.4412110.69360.34769157.45800.7898980.33212
31.0100.000000-0.0012913.190000e-070.00009510525.3103500.20470.0179533.59850.4708430.18173
467.097.901365-0.0246584.110000e-070.0001178489.9736350.72590.6370123.96810.8209690.38071
51.0100.000000-0.003282-1.680000e-060.0001218209.1180720.08280.00101129.01800.5500450.29700
61.0100.000000-0.000464-4.700000e-060.00006914356.7511500.05630.0745147.93190.4792240.30086
71.0100.000000-0.001045-5.240000e-060.0001476777.4372310.62000.49655125.59400.7478740.33374
81.0100.000000-0.0009142.560000e-070.00006914367.3494900.01260.05018141.74500.5635600.21974
91.0100.000000-0.0023207.490000e-070.00008611570.2043300.62300.38188153.86400.7793080.38723
S11S8S9S10S2S1S3S4S5S7S6
13161.0100.000000-0.0007951.680000e-070.00008411870.6215500.29940.08610144.80900.5463400.19773
13171.0100.000000-0.0005035.760000e-070.00009011037.0461700.16720.08820130.60200.5423560.24538
13181.0100.0000000.000898-1.340000e-070.00008112323.1038200.04130.10025135.08300.6305800.33617
13191.0100.000000-0.000250-1.460000e-050.0001327574.5011370.34020.1413544.65690.5319330.23101
132031.098.163694-0.0063702.210000e-060.0001327562.1485800.39840.0104963.34200.6526750.17039
132145.083.649713-0.0002583.100000e-070.00009610397.9489200.47980.34833141.04500.6926670.29576
132261.099.687717-0.0019601.870000e-060.0001476771.4201480.63760.0056869.49020.7919070.42194
13231.0100.000000-0.0066727.390000e-070.00008911161.5968200.41800.18798135.62700.5992730.25503
13241.0100.000000-0.001602-1.510000e-070.0001049577.7221850.52970.57872126.02900.7024640.31950
1325253.098.565888-0.001718-4.720000e-070.0001178475.4486470.62750.44497152.15600.7444650.29932